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Journal ArticleDOI

Microarray data normalization and transformation

John Quackenbush
- 01 Dec 2002 - 
- Vol. 32, Iss: 4, pp 496-501
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TLDR
This review focuses on the much more mundane but indispensable tasks of 'normalizing' data from individual hybridizations to make meaningful comparisons of expression levels, and of 'transforming' them to select genes for further analysis and data mining.
Abstract
Underlying every microarray experiment is an experimental question that one would like to address. Finding a useful and satisfactory answer relies on careful experimental design and the use of a variety of data-mining tools to explore the relationships between genes or reveal patterns of expression. While other sections of this issue deal with these lofty issues, this review focuses on the much more mundane but indispensable tasks of 'normalizing' data from individual hybridizations to make meaningful comparisons of expression levels, and of 'transforming' them to select genes for further analysis and data mining.

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Citations
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Journal ArticleDOI

The analysis of Lupinus albus root proteome revealed cytoskeleton altered features due to long-term boron deficiency.

TL;DR: The adaptive responses of Lupinus albus roots to long-term B deficiency are analyzed, and detected changes in cytoskeletal associated proteins indicate altered cytOSkeletal biosynthesis and suggest that B may have an important contribution in this process.
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Improved production of secreted heterologous enzyme in Bacillus subtilis strain MGB874 via modification of glutamate metabolism and growth conditions

TL;DR: High levels of production of alkaline cellulase Egl-237 are found with the reduced-genome strain 874∆rocG and using the NH3-pH auxostat fermentation, possibly due to improved glutamate synthesis and enhanced generation of metabolism energy.
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Opa Interacting Protein 5 (OIP5) Is a Novel Cancer-testis Specific Gene in Gastric Cancer

TL;DR: Using a combination of LMD and microarray, OIP5 was identified as a cancer-testis specific gene and may be a novel immunotherapy target for patients with gastric cancer.
Journal ArticleDOI

The 'yeast cell wall chip' - a tool to analyse the regulation of cell wall biogenesis in Saccharomyces cerevisiae.

TL;DR: The design and production of a gene microarray, called the 'yeast cell wall chip', specifically tailored to investigate cell wall functions, is described, which has been validated and shown to be useful to address gene involvement in the regulation of the response to cell wall damage in yeast.
Journal ArticleDOI

A global analysis of adaptive evolution of operons in cyanobacteria.

TL;DR: The results suggest that while in situ formation and vertical descent may be a dominant mechanism of operon evolution in cyanobacteria, optimization of intergenic spacing and co-regulation are part of an ongoing process in the life-cycle of operons.
References
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Journal ArticleDOI

Cluster analysis and display of genome-wide expression patterns

TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Book

Data Reduction and Error Analysis for the Physical Sciences

TL;DR: In this paper, Monte Carlo techniques are used to fit dependent and independent variables least squares fit to a polynomial least-squares fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
Journal ArticleDOI

Data Reduction and Error Analysis for the Physical Sciences.

TL;DR: Numerical methods matrices graphs and tables histograms and graphs computer routines in Pascal and Monte Carlo techniques dependent and independent variables least-squares fit to a polynomial least-square fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
Journal ArticleDOI

Robust Locally Weighted Regression and Smoothing Scatterplots

TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.
Book

Regression Analysis by Example

TL;DR: Simple linear regression Multiple linear regression Regression Diagnostics: Detection of Model Violations Qualitative Variables as Predictors Transformation of Variables Weighted Least Squares The Problem of Correlated Errors Analysis of Collinear Data Biased Estimation of Regression Coefficients Variable Selection Procedures Logistic Regression Appendix References as discussed by the authors
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